Tootfinder

Fair Rent Division: New Budget and Rent Constraints
Rohith Reddy Gangam, Shayan Taherijam, Vijay V. Vazirani
https://arxiv.org/abs/2510.05434 https://arxiv…

Fair Rent Division: New Budget and Rent Constraints
We study the classical rent division problem, where $n$ agents must allocate $n$ indivisible rooms and split a fixed total rent $R$. The goal is to compute an envy-free (EF) allocation, where no agent prefers another agent's room and rent to their own. This problem has been extensively studied under standard assumptions, where efficient algorithms for computing EF allocations are known. We extend this framework by introducing two practically motivated constraints: (i) lower and upper bounds o…

Pricing Short-Circuit Current via a Primal-Dual Formulation for Preserving Integrality Constraints
Peng Wang, Luis Badesa
https://arxiv.org/abs/2510.05293 https://

Pricing Short-Circuit Current via a Primal-Dual Formulation for Preserving Integrality Constraints
Synchronous Generators (SGs) currently provide important levels of Short-Circuit Current (SCC), a critical ancillary service that ensures line protections trip during short-circuit faults. Given the ongoing replacement of SGs by power-electronics-based generation, which have a hard limit for current injection, it has become relevant to optimize the procurement of SCC provided by remaining SGs. Pricing this service is however challenging due to the integrality constraints in Unit Commitment (UC)…

from my link log —
Should CSS be a constraint system instead?
https://pavpanchekha.com/blog/why-css-bad.html
saved 2025-12-06 https://

Constraints on dark matter models from the stellar cores observed in ultra-faint dwarf galaxies: Self-interacting dark matter
Jorge Sanchez Almeida (Instituto de Astrofisica de Canarias, La Laguna, Tenerife, E-38200, Spain, Departamento de Astrofisica, Universidad de La Laguna, Spain)
https://arxiv.org/abs/2510.05682

Constraints on dark matter models from the stellar cores observed in ultra-faint dwarf galaxies: Self-interacting dark matter
It has been proposed that the stellar cores observed in ultra-faint dwarf (UFD) galaxies reflect underlying dark matter (DM) cores that cannot be formed by stellar feedback acting on collisionless cold dark matter (CDM) halos. Assuming this claim is correct, we investigate the constraints that arise if such cores are produced by self-interacting dark matter (SIDM). We derive the range of SIDM cross-sections (sigma/m) required to reproduce the observed core sizes. These can result from halos in …

Observational constraints on f(Q,T) gravity from the mass-radius relation and stability of compact stars
S. K. Maurya, Abdul Aziz, Ksh. Newton Singh, G. Mustafa, Y. Sekhmani, Saibal Ray
https://arxiv.org/abs/2510.06003

Observational constraints on f(Q,T) gravity from the mass-radius relation and stability of compact stars
In this investigation we examine the astrophysical consequences of the influence of pressure anisotropy on the physical properties of observed pulsars within the background of $f(Q,T)$ gravity by choosing a specific form $f(Q, T)=ψ_1\, Q + ψ_2 T$, where $ψ_1$ and $ψ_2$ are the model parameters. Initially, we solve the modified field equations for anisotropic stellar configurations by assuming the physically valid metric potential along with anisotropic function for the distribution of the i…

Multiprobe constraints on early and late time dark energy
Alexander Reeves, Simone Ferraro, Andrina Nicola, Alexandre Refregier
https://arxiv.org/abs/2510.06114 https://

Multiprobe constraints on early and late time dark energy
We perform a multiprobe analysis combining cosmic microwave background (CMB) data from Planck and the Atacama Cosmology Telescope (ACT), ACT CMB lensing, and large-scale structure (LSS) measurements from the Dark Energy Spectroscopic Instrument (DESI), including DESI Legacy Imaging Survey (LS) galaxies and baryon acoustic oscillations (BAOs). We present the first $5\times2$pt analysis of ACT DR6 lensing, DESI LS, and Planck ISW. Within $Λ$CDM, this yields $S_8 = σ_8(Ω_m/0.3)^{0.5} = 0.819 \p…

Block Communications announces that The Pittsburgh Post-Gazette will cease publication May 3; the closure will not affect its sister newspaper, The Toledo Blade (Mark Walker/New York Times)
https://www.nytimes.com/2026/01/07/business/media/pittsburgh-po…

Pittsburgh Post-Gazette Announces It Will Cease Operations
The family-owned company that operates the newspaper cited mounting losses and labor constraints. A final edition is expected on Sunday, May 3.

Downsized and Compromised?: Assessing the Faithfulness of Model Compression
Moumita Kamal, Douglas A. Talbert
https://arxiv.org/abs/2510.06125 https://arxi…

Downsized and Compromised?: Assessing the Faithfulness of Model Compression
In real-world applications, computational constraints often require transforming large models into smaller, more efficient versions through model compression. While these techniques aim to reduce size and computational cost without sacrificing performance, their evaluations have traditionally focused on the trade-off between size and accuracy, overlooking the aspect of model faithfulness. This limited view is insufficient for high-stakes domains like healthcare, finance, and criminal justice, w…

Fascinated at how Wikidata's property constraints push particular models.
The capture of Maduro has different instance values, eg both "military intervention" and "kidnapping" (with a "disputed by" qualifier).
But the (disputed) inclusion then tries to push the use of perpetrator/victim values, rather than a neutral "participant".
(Wikidata property values have highly contextual meanings beyond simple labels... but editors are sti…

Adaptive Dynamics Planning for Robot Navigation
Lu Yuanjie, Mao Mingyang, Xu Tong, Wang Linji, Lin Xiaomin, Xiao Xuesu
https://arxiv.org/abs/2510.05330 https://

Adaptive Dynamics Planning for Robot Navigation
Autonomous robot navigation systems often rely on hierarchical planning, where global planners compute collision-free paths without considering dynamics, and local planners enforce dynamics constraints to produce executable commands. This discontinuity in dynamics often leads to trajectory tracking failure in highly constrained environments. Recent approaches integrate dynamics within the entire planning process by gradually decreasing its fidelity, e.g., increasing integration steps and reduci…

Recovery of the second law in fully quantum thermodynamics
Naoto Shiraishi, Ryuji Takagi
https://arxiv.org/abs/2510.05642 https://arxiv.org/pdf/2510.05642

Recovery of the second law in fully quantum thermodynamics
Quantum thermodynamics investigates how robust the second law of thermodynamics serves as the unique fundamental law in the small quantum world. To tackle this problem, the quantum coherence constitutes a major difficulty of investigations, which provides severe constraints hindering the recovery of a single thermodynamic potential. Here we solve this long-standing problem of quantum information theory by revealing that the state convertibility under thermal operations is fully characterized by…

TDCOSMO 2025 - Cosmological constraints from #StrongLensing time delays: https://www.aanda.org/articles/aa/full_html/2025/12/aa55801-25/aa55801-25.html -> A speed camera for the universe: https://www.u-tokyo.ac.jp/focus/en/press/z0508_00434.html - researchers exploit gravitational lensing to see how fast the universe is really expanding.

VeriGuard: Enhancing LLM Agent Safety via Verified Code Generation
Lesly Miculicich, Mihir Parmar, Hamid Palangi, Krishnamurthy Dj Dvijotham, Mirko Montanari, Tomas Pfister, Long T. Le
https://arxiv.org/abs/2510.05156

VeriGuard: Enhancing LLM Agent Safety via Verified Code Generation
The deployment of autonomous AI agents in sensitive domains, such as healthcare, introduces critical risks to safety, security, and privacy. These agents may deviate from user objectives, violate data handling policies, or be compromised by adversarial attacks. Mitigating these dangers necessitates a mechanism to formally guarantee that an agent's actions adhere to predefined safety constraints, a challenge that existing systems do not fully address. We introduce VeriGuard, a novel framework th…

Medium Access for Multi-Cell ISAC through Scheduling of Radar and Communication Tasks
Jo\~ao Henrique Inacio de Souza, Fabio Saggese, Kun Chen-Hu, Petar Popovski
https://arxiv.org/abs/2510.05821

Medium Access for Multi-Cell ISAC through Scheduling of Radar and Communication Tasks
This paper focuses on communication, radar search, and tracking task scheduling in multi-cell integrated sensing and communication (ISAC) networks under quality of service (QoS) constraints. We propose a medium access control framework multiplexing the tasks while optimizing radar scan patterns through an interference-aware assignment formulation. Simulations show that our solution guarantees target QoS with improved resource efficiency over baseline schemes, highlighting the benefits of coordi…

Improved Streaming Algorithm for Fair $k$-Center Clustering
Longkun Guo, Zeyu Lin, Chaoqi Jia, Chao Chen
https://arxiv.org/abs/2510.05937 https://arxiv.org…

Improved Streaming Algorithm for Fair $k$-Center Clustering
Many real-world applications pose challenges in incorporating fairness constraints into the $k$-center clustering problem, where the dataset consists of $m$ demographic groups, each with a specified upper bound on the number of centers to ensure fairness. Focusing on big data scenarios, this paper addresses the problem in a streaming setting, where data points arrive one by one sequentially in a continuous stream. Leveraging a structure called the $λ$-independent center set, we propose a one-p…

Can language models boost the power of randomized experiments without statistical bias?
Xinrui Ruan, Xinwei Ma, Yingfei Wang, Waverly Wei, Jingshen Wang
https://arxiv.org/abs/2510.05545

Can language models boost the power of randomized experiments without statistical bias?
Randomized experiments or randomized controlled trials (RCTs) are gold standards for causal inference, yet cost and sample-size constraints limit power. Meanwhile, modern RCTs routinely collect rich, unstructured data that are highly prognostic of outcomes but rarely used in causal analyses. We introduce CALM (Causal Analysis leveraging Language Models), a statistical framework that integrates large language models (LLMs) predictions with established causal estimators to increase precision whil…

Learning-based model predictive control with moving horizon state estimation for autonomous racing
Yassine Kebbati, Andreas Rauh, Naima Ait-Oufroukh, Dalil Ichalal, Vincent Vigneron
https://arxiv.org/abs/2510.05366

Learning-based model predictive control with moving horizon state estimation for autonomous racing
This paper addresses autonomous racing by introducing a real-time nonlinear model predictive controller (NMPC) coupled with a moving horizon estimator (MHE). The racing problem is solved by an NMPC-based off-line trajectory planner that computes the best trajectory while considering the physical limits of the vehicle and circuit constraints. The developed controller is further enhanced with a learning extension based on Gaussian process regression that improves model predictions. The proposed c…

Constraints on Radial Gas Flows in the Milky Way Disk Revealed by Large Stellar Age Catalogs
James W. Johnson
https://arxiv.org/abs/2510.05223 https://arxi…

Constraints on Radial Gas Flows in the Milky Way Disk Revealed by Large Stellar Age Catalogs
Disk galaxies like the Milky Way are expected to experience gas flows carrying matter toward their centers. This paper investigates the role of these radial gas flows in models of Galactic chemical evolution (GCE). We follow five different parameterizations of the Galactocentric radial velocity, $v_{r,g}$, of the interstellar medium (ISM). Relative to the $v_{r,g}=0$ limit, all models predict stellar metallicity to decline less significantly with age in the outer disk and more significantly in …

Stochastic BDDC algorithms
Xuemin Tu, Jinjin Zhang
https://arxiv.org/abs/2510.05993 https://arxiv.org/pdf/2510.05993

Stochastic BDDC algorithms
Stochastic balancing domain decomposition by constraints (BDDC) algorithms are developed and analyzed for the sampling of the solutions of linear stochastic elliptic equations with random coefficients. Different from the deterministic BDDC algorithms, the stochastic BDDC algorithms have online and offline stages. At the offline stage, the Polynomial Chaos (PC) expansions of different components of the BDDC algorithms are constructed based on the subdomain local parametrization of the stochastic…

Rivaling Transformers: Multi-Scale Structured State-Space Mixtures for Agentic 6G O-RAN
Farhad Rezazadeh, Hatim Chergui, Merouane Debbah, Houbing Song, Dusit Niyato, Lingjia Liu
https://arxiv.org/abs/2510.05255

Rivaling Transformers: Multi-Scale Structured State-Space Mixtures for Agentic 6G O-RAN
In sixth-generation (6G) Open Radio Access Networks (O-RAN), proactive control is preferable. A key open challenge is delivering control-grade predictions within Near-Real-Time (Near-RT) latency and computational constraints under multi-timescale dynamics. We therefore cast RAN Intelligent Controller (RIC) analytics as an agentic perceive-predict xApp that turns noisy, multivariate RAN telemetry into short-horizon per-User Equipment (UE) key performance indicator (KPI) forecasts to drive antici…

Integrating Weather and Land Cover Data into Geospatial Impact Evaluations
Elinor Benami, Mike Cecil, Anna Josephson, Gina Maskell, Jeffrey D. Michler
https://arxiv.org/abs/2510.05108

Integrating Weather and Land Cover Data into Geospatial Impact Evaluations
Integrating gridded weather and earth observation data into impact evaluations holds great promise. It allows researchers to capture environmental context, external shocks, and even to measure outcomes (e.g., land cover change, agricultural production) that surveys might miss due to spatial or temporal data collection constraints. However, with great power comes great responsibility: the increasing ease of extracting time series from these datasets belies potentially complex geospatial and meas…

Sometimes I understand why people design new standards or formats when the existing ones can’t be extended (whether due to practical constraints, authority, or bureaucracy) or simply aren’t flexible enough to evolve. I think the XKCD comic doesn’t include that aspect.
And yes, maybe new standards will appear.
#nocontext

Microwave electrometry with quantum-limited resolutions in a Rydberg atom array
Yao-Wen Zhang, De-Sheng Xiang, Ren Liao, Hao-Xiang Liu, Biao Xu, Peng Zhou, Yijia Zhou, Kuan Zhang, Lin Li
https://arxiv.org/abs/2512.05413 https://arxiv.org/pdf/2512.05413 https://arxiv.org/html/2512.05413
arXiv:2512.05413v1 Announce Type: new
Abstract: Microwave (MW) field sensing is foundational to modern technology, yet its evolution, reliant on classical antennas, is constrained by fundamental physical limits on field, temporal, and spatial resolutions. Here, we demonstrate an MW electrometry that simultaneously surpasses these constraints by using individual Rydberg atoms in an optical tweezer array as coherent sensors. This approach achieves a field sensitivity within 13% of the standard quantum limit, a response time that exceeds the Chu limit by more than 11 orders of magnitude, and in-situ near-field mapping with {\lambda}/3000 spatial resolution. This work establishes Rydberg-atom arrays as a powerful platform that unites quantum-limited sensitivity, nanosecond-scale response time, and sub-micrometer resolution, opening new avenues in quantum metrology and precision electromagnetic field imaging.
toXiv_bot_toot

Replaced article(s) found for cs.RO. https://arxiv.org/list/cs.RO/new
[1/2]:
- Interpreting Behaviors and Geometric Constraints as Knowledge Graphs for Robot Manipulation Control
Chen Jiang, Allie Wang, Martin Jagersand

Robust Pricing and Hedging of American Options in Continuous Time
Ivan Guo, Jan Ob\l\'oj
https://arxiv.org/abs/2510.05463 https://arxiv.org/pdf/2510.05…

Robust Pricing and Hedging of American Options in Continuous Time
We consider the robust pricing and hedging of American options in a continuous time setting. We assume asset prices are continuous semimartingales, but we allow for general model uncertainty specification via adapted closed convex constraints on the volatility. We prove the robust pricing-hedging duality. When European options with given prices are available for static trading, we show that duality holds against richer models where these options are traded dynamically. Our proofs rely on probab…

An approach using geometric diagrams to generic Bell inequalities with multiple observables
Junghee Ryu, Jinhyoung Lee, Hoon Ryu
https://arxiv.org/abs/2510.05622 https://…

An approach using geometric diagrams to generic Bell inequalities with multiple observables
We extend the generic Bell inequalities suggested by Son, Lee, and Kim [Phys. Rev. Lett. 96, 060406 (2006)] to incorporate multiple observables for tripartite systems and introduce a geometric methodology for calculating classical upper bounds of the inequalities. Our method transforms the problem of finding the classical upper bounds into identifying constraints in linear congruence relations. Using this approach, we derive the upper bounds for scenarios with three and four observables per par…

JWST-TST DREAMS - NIRSpec/PRISM Transmission Spectroscopy of the Habitable Zone Planet TRAPPIST-1 e & Secondary Atmosphere Constraints for the Habitable Zone Planet TRAPPIST-1 e / The Photochemical Plausibility of Warm Exo-Titans Orbiting M Dwarf Stars: #TRAPPIST-1e, an Earth-sized, habitable-zone exoplanet: https://news.arizona.edu/news/new-look-trappist-1e-earth-sized-habitable-zone-exoplanet

I still think Wirtz was offside and hearing the commentators say that the semi-automated offsides technology is not in the same room as VAR and that they have to relay back and forth the assisting player and scoring player's numbers... is bananas!
Different company because of partnership constraints, but the SAOT at other major tournaments is instantaneous. Now we eventually get an image, but not vision of the ball at the moment the image purports to represent. PGMOL incompetence👏 …

Today, I designed, built and launched a small software application within very strict financial, security, hardware and software constraints.
Then I helped people with all levels of tech skill, and different hardware and software configurations, get it running with their own setups.
That's a lot of corporate speak and being vague, but it feels good to have it out in the world helping people: letting them get a very specific thing done better.

A Predictive and Sampled-Data Barrier Method for Safe and Efficient Quadrotor Control
Ming Gao, Zhanglin Shangguan, Shuo Liu, Liang Wu, Bo Yang, Wei Xiao
https://arxiv.org/abs/2510.05456

A Predictive and Sampled-Data Barrier Method for Safe and Efficient Quadrotor Control
This paper proposes a cascaded control framework for quadrotor trajectory tracking with formal safety guarantees. First, we design a controller consisting of an outer-loop position model predictive control (MPC) and an inner-loop nonlinear attitude control, enabling decoupling of position safety and yaw orientation. Second, since quadrotor safety constraints often involve high relative degree, we adopt high order control barrier functions (HOCBFs) to guarantee safety. To employ HOCBFs in the MP…

Validation of the DESI-DR1 3x2-pt analysis: scale cut and shear ratio tests
N. Emas, A. Porredon, C. Blake, J. DeRose, J. Aguilar, S. Ahlen, D. Bianchi, D. Brooks, F. J. Castander, T. Claybaugh, A. Cuceu, A. de la Macorra, A. Dey, B. Dey, P. Doel, S. Ferraro, J. E. Forero-Romero, C. Garcia-Quintero, E. Gazta\~naga, S. Gontcho A Gontcho, G. Gutierrez, S. Heydenreich, K. Honscheid, D. Huterer, M. Ishak, S. Joudaki, R. Joyce, E. Jullo, S. Juneau, R. Kehoe, D. Kirkby, T. Kisner, A. Kremin,…

Validation of the DESI-DR1 3x2-pt analysis: scale cut and shear ratio tests
Combined survey analyses of galaxy clustering and weak gravitational lensing (3x2-pt studies) will allow new and accurate tests of the standard cosmological model. However, careful validation is necessary to ensure that these cosmological constraints are not biased by uncertainties associated with the modelling of astrophysical or systematic effects. In this study we validate the combined 3x2-pt analysis of the Dark Energy Spectroscopic Instrument Data Release 1 (DESI-DR1) spectroscopic galaxy …

This is the best critique of SF's Family Zoning Plan I've seen, from Fernando Martí, who knows his stuff.
“Zoning is not the primary constraint to construction today — not in SF where it costs $800,000 or more to build a unit of housing. Nor is environmental review or planning approvals. If these were the constraints to production, then we wouldn’t have tens of thousands of already approved market-rate units unable to get construction financing”

Stable Robot Motions on Manifolds: Learning Lyapunov-Constrained Neural Manifold ODEs
David Boetius, Abdelrahman Abdelnaby, Ashok Kumar, Stefan Leue, Abdalla Swikir, Fares J. Abu-Dakka
https://arxiv.org/abs/2510.05707

Stable Robot Motions on Manifolds: Learning Lyapunov-Constrained Neural Manifold ODEs
Learning stable dynamical systems from data is crucial for safe and reliable robot motion planning and control. However, extending stability guarantees to trajectories defined on Riemannian manifolds poses significant challenges due to the manifold's geometric constraints. To address this, we propose a general framework for learning stable dynamical systems on Riemannian manifolds using neural ordinary differential equations. Our method guarantees stability by projecting the neural vector field…

Quantum Annealing for Realistic Traffic Flow Optimization: Clustering and Data-Driven QUBO
Ren\'ata Rusn\'akov\'a, Martin Chovanec, Juraj Gazda
https://arxiv.org/abs/2510.06053

Quantum Annealing for Realistic Traffic Flow Optimization: Clustering and Data-Driven QUBO
Managing city traffic is a complex NP-hard problem where traditional methods often fail to scale. We present a data-driven approach that reformulates traffic optimization as a Quadratic Unconstrained Binary Optimization, capturing both congestion reduction and travel-time efficiency. The model integrates simulated realistic mobility data, multiple routing alternatives, and analytically derived penalty constraints. To address large networks, we apply Leiden clustering to preserve critical conges…

Pete Hegseth, told soldiers under his command in Iraq to
ignore legal advice about when they were permitted to kill enemy combatants under their rules of engagement.
The anecdote is contained in a book Hegseth wrote last year in which he also repeatedly railed against the
constraints placed on “American warfighters” by the laws of war and the Geneva conventions.
Hegseth is currently under scrutiny for a 2 September attack on a boat purportedly carrying drugs in the Ca…

ILLUSTRating red nugget assembly through observations and simulations
Micheli T. Moura, Anna Ferr\'e-Mateu, Ana L. Chies-Santos, Cristina Furlanetto, Michael A. Beasley
https://arxiv.org/abs/2510.05312

ILLUSTRating red nugget assembly through observations and simulations
The properties of massive and compact early-type galaxies provide important constraints on early galaxy formation. Among these, massive relic galaxies, characterized by old stellar populations and minimal late-time accretion, are considered preserved compact galaxies from the high-$z$ Universe. We investigate compact and massive galaxies (CMGs) using the TNG50 cosmological simulation, applying uniform selection criteria matching observational surveys at $z=0$, $z=0.3$, and $z=0.7$, enabling dir…

Didn’t know these quotes, but I love writing code ina world of constraints.
(From “math with bad drawings”)

Sutskever: We need new inductive constraints.
Marcus: That means neurosymbolic architectures! He said it. I was right all along. Why didn't anybody listen to me, the modern Cassandra? Woe is me.

You may know the project management triangle.
https://en.wikipedia.org/wiki/Project_management_triangle
It puts the quality of a product in the center and pictures the scope, budget and time as constraints.
There is this other triagle I see for companies:

Central Massive Black Holes Are Not Ubiquitous in Local Low-Mass Galaxies
Fan Zou, Elena Gallo, Anil C. Seth, Edmund Hodges-Kluck, David Ohlson, Tommaso Treu, Vivienne F. Baldassare, W. N. Brandt, Jenny E. Greene, Piero Madau, Dieu D. Nguyen, Richard M. Plotkin, Amy E. Reines, Alberto Sesana, Jong-Hak Woo, Jianfeng Wu
https://arxiv.org/abs…

Central Massive Black Holes Are Not Ubiquitous in Local Low-Mass Galaxies
The black-hole occupation fraction ($f_\mathrm{occ}$) defines the fraction of galaxies that harbor central massive black holes (MBHs), irrespective of their accretion activity level. While it is widely accepted that $f_\mathrm{occ}$ is nearly 100% in local massive galaxies with stellar masses $M_\star \gtrsim 10^{10}~M_\odot$, it is not yet clear whether MBHs are ubiquitous in less-massive galaxies. In this work, we present new constraints on $f_\mathrm{occ}$ based on over 20 years of Chandra i…

ChatGPT Atlas hands-on: generally able to interpret instructions and navigate simple menus, but "technical constraints on session length" are a limiting factor (Kyle Orland/Ars Technica)
https://arstechnica.com/features/2025/

We let OpenAI’s “Agent Mode” surf the web for us—here’s what happened
From scanning emails to building fansites, Atlas can ably automate some web-based tasks.

I think we can actually prove that this constraint is the *only* constraint that can preserve freedom:
1. There will exist actors in a system who will wish to take advantage of others. Evolution drives survival and one strategy for increasing survival in an altruistic society is to become a parasite.
2. Expecting exploitative dynamics, a system needs to have a set of rules to manage exploitation.
3. If the set of rules is static it will lack the requisite variety necessary to manage the infinite possible behavior of humans so the system will fail.
4. If the system is dynamic then it must have a rule set about how it's own rules are updated. This would make the system recursive, which makes the system at least as complex as mathematics. Any system at least as complex as mathematics is necessarily either incomplete or inconsistent (Gödel's incompleteness theorem). If the system is incomplete, then constraints can be evaded which then allow a malicious agent to seize control of the system and update the rules for their own benefit. If constraints are incomplete, then a malicious agent can take advantage of others within the system.
5. Therefore, no social system can possibly protect freedom unless there exists a single metasystemic constraint (that the system must be optional) allowing for the system to be abandoned when compromised.
Oh, you might say, but this just means you have to infinitely abandon systems. Sure, but there's an evolutionary advantage to cooperation so there's evolutionary pressure to *not* be a malicious actor. So a malicious actor being able to compromise the whole system is likely to be a much more rare event. Compromising a system is a lot of work, so the first thing a malicious actor would want to do is preserve that work. They would want to lock you in. The most important objective to a malicious actor compromising a system would be to violate that metasystemic constraint, or all of their work goes out the window when everyone leaves.
And now you understand why borders exist, why fascists are obsessed with maintaining categories like gender, race, ethnicity, etc. This is why even Democrats like Newsom are on board with putting houseless people in concentration camps. And this is why the most important thing anarchists promote is the ability to choose not to be part of any of that.

Ukrainian Forces in Mirnohrad face operational encirclement amid severe logistics constraints, MP says: https://benborges.xyz/2025/12/23/ukrainian-forces-in-mirnohrad-face.html

Manchester’s Local Plan – responding to the consultation
Local Plans are what guide the pattern of a land use and and building across a council area.  In the case of Greater Manchester (excluding Stockport), the Joint Strategic Plan, Places for Everyone sets the scene, as does the government's National Planning Policy Framework.  That means that there are some very real constraints on what can be put into a so-called Local Plan (not very local - in the case of…

Manchester’s Local Plan – responding to the consultation
UPDATE!  11 Nov.  We have now submitted a revised version.  It adds some answers to questions we didn’t address in the previously published draft, and has some additions to some of the other …

How constraints fuel creativity!
https://www.youtube.com/watch?v=HoUMdM3x5Dw

“Israeli soldiers have described a free-for-all in Gaza and a breakdown in norms and legal constraints, with civilians killed at the whim of individual officers, according to testimony in a TV documentary.
“If you want to shoot without restraint, you can,” Daniel, the commander of an Israel Defense Forces (IDF) tank unit, says in Breaking Ranks: Inside Israel’s War, due to be broadcast in the UK on ITV on Monday evening.
Some of the IDF soldiers who talked to the programme reques…

Oof, fuck microsoft.
But also, there's no reason to use permissive licenses any more. "Open source" has taken over the world. We no longer have to work with billion-dollar companies in order to get our stuff used. Now we need to protect ourselves from being taken advantage of by them.
https://

NaViL: Rethinking Scaling Properties of Native Multimodal Large Language Models under Data Constraints
Changyao Tian, Hao Li, Gen Luo, Xizhou Zhu, Weijie Su, Hanming Deng, Jinguo Zhu, Jie Shao, Ziran Zhu, Yunpeng Liu, Lewei Lu, Wenhai Wang, Hongsheng Li, Jifeng Dai
https://arxiv.org/abs/2510.08565 …

NaViL: Rethinking Scaling Properties of Native Multimodal Large Language Models under Data Constraints
Compositional training has been the de-facto paradigm in existing Multimodal Large Language Models (MLLMs), where pre-trained vision encoders are connected with pre-trained LLMs through continuous multimodal pre-training. However, the multimodal scaling property of this paradigm remains difficult to explore due to the separated training. In this paper, we focus on the native training of MLLMs in an end-to-end manner and systematically study its design space and scaling property under a practica…

Remoteness, order, size and connectivity constraints in digraphs
Sufiyan Mallu
https://arxiv.org/abs/2510.08841 https://arxiv.org/pdf/2510.08841

Remoteness, order, size and connectivity constraints in digraphs
Let \( D \) be a strongly connected digraph. The average distance of a vertex \( v \) in \( D \) is defined as the arithmetic mean of the distances from \( v \) to all other vertices in \( D \). The remoteness \( ρ(D) \) of \( D \) is the maximum of the average distances of the vertices in \( D \). In this paper, we provide a sharp upper bound on the remoteness of a strong digraph with given order, size, and vertex-connectivity. We then characterise the extremal digraphs that maximise remote…

"In summary, #AGI, as commonly conceived, will not happen because it ignores the physical constraints of computation, the exponential costs of linear progress, and the fundamental limits we are already encountering. Superintelligence is a fantasy because it assumes that intelligence can recursively self-improve without bound, ignoring the physical and economic realities that constrain all systems. …

Multi-Armed Bandits with Minimum Aggregated Revenue Constraints
Ahmed Ben Yahmed, Hafedh El Ferchichi, Marc Abeille, Vianney Perchet
https://arxiv.org/abs/2510.12523 https://

Multi-Armed Bandits with Minimum Aggregated Revenue Constraints
We examine a multi-armed bandit problem with contextual information, where the objective is to ensure that each arm receives a minimum aggregated reward across contexts while simultaneously maximizing the total cumulative reward. This framework captures a broad class of real-world applications where fair revenue allocation is critical and contextual variation is inherent. The cross-context aggregation of minimum reward constraints, while enabling better performance and easier feasibility, intro…

Robust Closed-Form Control for MIMO Nonlinear Systems under Conflicting Time-Varying Hard and Soft Constraints
Farhad Mehdifar, Charalampos P. Bechlioulis, Dimos V. Dimarogonas
https://arxiv.org/abs/2510.11393

Robust Closed-Form Control for MIMO Nonlinear Systems under Conflicting Time-Varying Hard and Soft Constraints
This paper introduces a novel robust closed-form control law to handle time-varying hard and soft constraints in uncertain high-relative-degree nonlinear MIMO systems. These constraints represent spatiotemporal specifications in mechanical systems' operational space, with hard constraints ensuring safety-critical requirements and soft constraints encoding performance or task objectives. Initially, all constraints are consolidated into two separate scalar time-varying hard and soft constraint fu…

First simultaneous global QCD analysis of kaon and pion parton distributions with lattice QCD constraints
P. C. Barry, Chueng-Ryong Ji, W. Melnitchouk, N. Sato, Fernanda Steffens
https://arxiv.org/abs/2510.11979

First simultaneous global QCD analysis of kaon and pion parton distributions with lattice QCD constraints
We perform the first simultaneous global QCD analysis of pion and kaon parton distribution functions (PDFs), constrained by pion- and kaon-induced Drell-Yan (DY) and leading neutron electroproduction data, together with lattice QCD data on pion and kaon PDF moments. The analysis indicates a softer valence $\bar u$ distribution in the $K^-$ than in the $π^-$, and a significantly more peaked valence $s$-quark density in $K^-$ compared with the $\bar u$. The effective exponent governing the high-…

Industry executives say nearly all major memory chipmakers are running at or near full capacity, with 2026 production slots almost "sold out" due to AI demand (Nikkei Asia)
https://asia.nikkei.com/business/technolog…

Rampant AI demand throws the memory chip market into turmoil
Supply constraints spark warnings of price rises and launch delays for consumer electronics

Because #accessibility is out of scope for Baseline, devs may not know how poorly supported a feature is and miss an opportunity to vote for things that are barriers to users and risks to orgs.
“Vote for the web features you want to see”
https://

Localized structures in two-field systems: exact solutions in the presence of Lorentz symmetry breaking and explicit connection with geometric constraints
G. H. Bandeira, D. Bazeia, G. S. Santiago, Ya. Shnir
https://arxiv.org/abs/2510.07012

Localized structures in two-field systems: exact solutions in the presence of Lorentz symmetry breaking and explicit connection with geometric constraints
We investigate a class of models described by two real scalar fields in two-dimensional spacetime. The study focuses mainly on the presence of exact static solutions which satisfy the first-order formalism, in models constructed to engender Lorentz symmetry violation. We start by exploring a direct connection between Lorentz breaking and geometric constraint, as experimentally examined in the case of domain walls in geometrically constrained magnetic materials. By means of a specific choice of …

🌊 Offshore Pumped Hydro Could Solve Clean Energy's Biggest Problem
https://oilprice.com/Energy/Energy-General/Offshore-Pumped-Hydro-Could-Solve-Clean-Energys-Biggest-Problem.html

Offshore Pumped Hydro Could Solve Clean Energy's Biggest Problem
An Italian startup is developing an offshore pumped hydro storage system that avoids the environmental and geographical constraints of traditional land-based dams, offering a potentially disruptive solution for long-duration energy storage and grid stability.

Constraints on inelastic dark matter from the CDEX-1B experiment
Y. F. Liang, L. T. Yang, Q. Yue, K. J. Kang, Y. J. Li, H. P. An, Greeshma C., J. P. Chang, H. Chen, Y. H. Chen, J. P. Cheng, J. Y. Cui, W. H. Dai, Z. Deng, Y. X. Dong, C. H. Fang, H. Gong, Q. J. Guo, T. Guo, X. Y. Guo, L. He, J. R. He, H. X. Huang, T. C. Huang, S. Karmakar, Y. S. Lan, H. B. Li, H. Y. Li, J. M. Li, J. Li, M. C. Li, Q. Y. Li, R. M. J. Li, X. Q. Li, Y. L. Li, B. Liao, F. K. Lin, S. T. Lin, J. X. Liu, R. Z. L…

Constraints on inelastic dark matter from the CDEX-1B experiment
We present limits on spin-independent inelastic WIMP-nucleus scattering using the 737.1 kg $\cdot$ day dataset from the CDEX-1B experiment. Expected nuclear recoil spectra for various inelastic WIMP masses $m_χ$ and mass splittings $δ$ are calculated under the standard halo model. An accurate background model of CDEX-1B is constructed by simulating all major background sources. The model parameters are then determined through maximum likelihood estimation and Markov Chain Monte Carlo fitting.…

I had missed that last month, the condo development in the south parking lot of Fairview Mall was scaled back (at least for the first phase)
It's now just 1 tower instead of 3, and it's a rental instead of condos.
It's a really bad market to sell condos right now, so it's not too surprising.

Moody Urbanity - Manmade Confinements ⛑️
情绪化城市 - 人造禁锢 ⛑️
📷 Pentax MX
🎞️ Kentmere Pan 400
#filmphotography #Photography #blackandwhite

At what point does anyone think it will be economically feasible for a government to speculatively decode bulk intercepts of circa 2025 traffic (using, say, 2048 bit RSA keys) using quantum computers?
As in you've got 100k qubits you're not otherwise using, and no real energy constraints.
Because I've seen that used as reason not to allow Royal Mint Court to be used by China.

HardcoreLogic: Challenging Large Reasoning Models with Long-tail Logic Puzzle Games
Jingcong Liang, Shijun Wan, Xuehai Wu, Siyuan Wang, Yitong Li, Qianglong Chen, Duyu Tang, Zhongyu Wei
https://arxiv.org/abs/2510.12563

HardcoreLogic: Challenging Large Reasoning Models with Long-tail Logic Puzzle Games
Large Reasoning Models (LRMs) have demonstrated impressive performance on complex tasks, including logical puzzle games that require deriving solutions satisfying all constraints. However, whether they can flexibly apply appropriate rules to varying conditions, particularly when faced with non-canonical game variants, remains an open question. Existing corpora focus on popular puzzles like 9x9 Sudoku, risking overfitting to canonical formats and memorization of solution patterns, which can mask…

The Atacama #Cosmology Telescope: DR6 maps / power spectra, likelihoods and ΛCDM parameters / constraints on extended cosmological models: https://iopscience.iop.org/article/10.1088/1475-7516/2025/11/061 / https://iopscience.iop.org/article/10.1088/1475-7516/2025/11/062 / https://iopscience.iop.org/article/10.1088/1475-7516/2025/11/063 -> ACT releases its final data, shaping the future of cosmology: https://www.eurekalert.org/news-releases/1106637

Probing Latent Knowledge Conflict for Faithful Retrieval-Augmented Generation
Linfeng Gao, Baolong Bi, Zheng Yuan, Le Wang, Zerui Chen, Zhimin Wei, Shenghua Liu, Qinggang Zhang, Jinsong Su
https://arxiv.org/abs/2510.12460

Probing Latent Knowledge Conflict for Faithful Retrieval-Augmented Generation
Retrieval-Augmented Generation (RAG) has emerged as a powerful paradigm to enhance the factuality of Large Language Models (LLMs). However, existing RAG systems often suffer from an unfaithfulness issue, where the model's response contradicts evidence from the retrieved context. Existing approaches to improving contextual faithfulness largely rely on external interventions, such as prompt engineering, decoding constraints, or reward-based fine-tuning. These works treat the LLM as a black box an…

Dynamic Regret Bounds for Online Omniprediction with Long Term Constraints
Yahav Bechavod, Jiuyao Lu, Aaron Roth
https://arxiv.org/abs/2510.07266 https://a…

Dynamic Regret Bounds for Online Omniprediction with Long Term Constraints
We present an algorithm guaranteeing dynamic regret bounds for online omniprediction with long term constraints. The goal in this recently introduced problem is for a learner to generate a sequence of predictions which are broadcast to a collection of downstream decision makers. Each decision maker has their own utility function, as well as a vector of constraint functions, each mapping their actions and an adversarially selected state to reward or constraint violation terms. The downstream dec…

Generalized Multi-Constraint Extremum Seeking
Alan Williams, Jorge Cort\'es, Alexander Scheinker
https://arxiv.org/abs/2510.06403 https://arxiv.org/pdf…

Generalized Multi-Constraint Extremum Seeking
We generalize the Safe Extremum Seeking algorithm to address the minimization of an unknown objective function subject to multiple unknown inequality and equality constraints, relying on recent results of gradient flow systems. These constraints may represent safety or other critical conditions. The proposed ES algorithm functions as a general nonlinear programming tool, offering practical maintenance of all constraints and semiglobal practical asymptotic stability, utilizing a Lyapunov argumen…

Observational Constraints on Chaplygin Gas Models in Non-Minimally Coupled Power Law $f(Q)$ Gravity with Quasars
Nakul Aggarwal, Ali Pourmand, Fatimah Shojai, Harish Parthasarathy
https://arxiv.org/abs/2510.12472

Observational Constraints on Chaplygin Gas Models in Non-Minimally Coupled Power Law $f(Q)$ Gravity with Quasars
In the framework of $f(Q)$ gravity, where gravity emerges from non-metricity $Q$, we explore the cosmological implications of its non-minimal coupling to matter. Inspired by the recent success of Chaplygin gas models in explaining dark energy, we consider a background fluid composed of baryonic matter, radiation, and a family of Chaplygin gas variants namely Generalized Chaplygin Gas (GCG), Modified Chaplygin Gas (MCG), and Variable Chaplygin Gas (VCG). We constrain these models with three rece…

Constraint-Guided Unit Test Generation for Machine Learning Libraries
Lukas Krodinger, Altin Hajdari, Stephan Lukasczyk, Gordon Fraser
https://arxiv.org/abs/2510.09108 https://

Constraint-Guided Unit Test Generation for Machine Learning Libraries
Machine learning (ML) libraries such as PyTorch and TensorFlow are essential for a wide range of modern applications. Ensuring the correctness of ML libraries through testing is crucial. However, ML APIs often impose strict input constraints involving complex data structures such as tensors. Automated test generation tools such as Pynguin are not aware of these constraints and often create non-compliant inputs. This leads to early test failures and limited code coverage. Prior work has investig…

Orientation Learning and Adaptation towards Simultaneous Incorporation of Multiple Local Constraints
Gaofeng Li, Peisen Xu, Ruize Wang, Qi Ye, Jiming Chen, Dezhen Song, Yanlong Huang
https://arxiv.org/abs/2510.07986

Orientation Learning and Adaptation towards Simultaneous Incorporation of Multiple Local Constraints
Orientation learning plays a pivotal role in many tasks. However, the rotation group SO(3) is a Riemannian manifold. As a result, the distortion caused by non-Euclidean geometric nature introduces difficulties to the incorporation of local constraints, especially for the simultaneous incorporation of multiple local constraints. To address this issue, we propose the Angle-Axis Space-based orientation representation method to solve several orientation learning problems, including orientation adap…

from my link log —
Let's take esoteric programming languages seriously.
https://arxiv.org/abs/2505.15327
saved 2025-10-11 https://dotat.at/:/XKTKR.…

Let's Take Esoteric Programming Languages Seriously
Esoteric programming languages are challenging to learn, but their unusual features and constraints may serve to improve programming ability. From languages designed to be intentionally obtuse (e.g. INTERCAL) to others targeting artistic expression (e.g. Piet) or exploring the nature of computation (e.g. Fractan), there is rich variety in the realm of esoteric programming languages. This essay examines the counterintuitive appeal of esoteric languages and seeks to analyse reasons for this popul…

Bridging the Physics-Data Gap with FNO-Guided Conditional Flow Matching: Designing Inductive Bias through Hierarchical Physical Constraints
Tsuyoshi Okita
https://arxiv.org/abs/2510.08295

Bridging the Physics-Data Gap with FNO-Guided Conditional Flow Matching: Designing Inductive Bias through Hierarchical Physical Constraints
Conventional time-series generation often ignores domain-specific physical constraints, limiting statistical and physical consistency. We propose a hierarchical framework that embeds the inherent hierarchy of physical laws-conservation, dynamics, boundary, and empirical relations-directly into deep generative models, introducing a new paradigm of physics-informed inductive bias. Our method combines Fourier Neural Operators (FNOs) for learning physical operators with Conditional Flow Matching (C…

Low-redshift constraints on structure growth from CMB lensing tomography
Andrea Rubiola, Matteo Zennaro, Carlos Garc\'ia-Garc\'ia, David Alonso
https://arxiv.org/abs/2510.09563

Low-redshift constraints on structure growth from CMB lensing tomography
We present constraints on the amplitude of matter fluctuations from the clustering of galaxies and their cross-correlation with the gravitational lensing convergence of the cosmic microwave background (CMB), focusing on low redshifts ($z\lesssim0.3$), where potential deviations from a perfect cosmological constant dominating the growth of structure could be more prominent. Specifically, we make use of data from the 2MASS photometric survey (\tmpz) and the \wisc galaxy survey, in combination wit…

Mean-Field Games with Constraints
Anran Hu, Zijiu Lyu
https://arxiv.org/abs/2510.11843 https://arxiv.org/pdf/2510.11843

Mean-Field Games with Constraints
This paper introduces a framework of Constrained Mean-Field Games (CMFGs), where each agent solves a constrained Markov decision process (CMDP). This formulation captures scenarios in which agents' strategies are subject to feasibility, safety, or regulatory restrictions, thereby extending the scope of classical mean field game (MFG) models. We first establish the existence of CMFG equilibria under a strict feasibility assumption, and we further show uniqueness under a classical monotonicity co…

Probing Dark Matter Interactions with Stellar Motion near Sagittarius A*
R. Andrew Gustafson, Ian M. Shoemaker, Volodymyr Takhistov
https://arxiv.org/abs/2510.07387 https://

Probing Dark Matter Interactions with Stellar Motion near Sagittarius A*
Stars orbiting Sgr A* at the Milky Way's center provide a unique laboratory to test gravity and dark matter (DM). We demonstrate that DM interactions in stellar interiors induce a novel momentum transfer force, altering orbits beyond gravitational effects. Using S2's 2000-2019 orbital data we derive the first astrophysical constraints on DM-nucleon scattering, excluding new sub-GeV parameter space. Stellar lifetime constraints over Myr timescales complement these, surpassing some direct detecti…

Physics-Informed Reinforcement Learning for Large-Scale EV Smart Charging Considering Distribution Network Voltage Constraints
Stavros Orfanoudakis, Frans Oliehoek, Peter Palesnky, Pedro P. Vergara
https://arxiv.org/abs/2510.12335

Physics-Informed Reinforcement Learning for Large-Scale EV Smart Charging Considering Distribution Network Voltage Constraints
Electric Vehicles (EVs) offer substantial flexibility for grid services, yet large-scale, uncoordinated charging can threaten voltage stability in distribution networks. Existing Reinforcement Learning (RL) approaches for smart charging often disregard physical grid constraints or have limited performance for complex large-scale tasks, limiting their scalability and real-world applicability. This paper introduces a physics-informed (PI) RL algorithm that integrates a differentiable power flow m…

Big Bang Nucleosynthesis constraints on space-time noncommutativity
Teodora Maria Matei, Cristian Croitoru, Tiberiu Harko
https://arxiv.org/abs/2510.10685 https://

Big Bang Nucleosynthesis constraints on space-time noncommutativity
We consider the implications of the modified dispersion relations, due to the noncommutativity of the spacetime, for a photon gas filling the early Universe in the framework of the Big Bang Nucleosynthesis (BBN) processes, during the period of light elements formation. We consider three types of deformations present in the dispersion relations for the radiation gas, from which we obtain the low temperature corrections to the energy density and pressure. The cosmological implications of the modi…

Do Large Language Models Respect Contracts? Evaluating and Enforcing Contract-Adherence in Code Generation
Soohan Lim, Joonghyuk Hahn, Hyunwoo Park, Sang-Ki Ko, Yo-Sub Han
https://arxiv.org/abs/2510.12047

Do Large Language Models Respect Contracts? Evaluating and Enforcing Contract-Adherence in Code Generation
Prevailing code generation benchmarks, such as HumanEval+ and MBPP+, primarily evaluate large language models (LLMs) with pass@k on functional correctness using well-formed inputs. However, they ignore a crucial aspect of real-world software: adherence to contracts-the preconditions and validity constraints that dictate how ill-formed inputs must be rejected. This critical oversight means that existing benchmarks fail to measure, and models consequently fail to generate, truly robust and reliab…

Efficient Perceptual Image Super Resolution: AIM 2025 Study and Benchmark
Bruno Longarela, Marcos V. Conde, Alvaro Garcia, Radu Timofte
https://arxiv.org/abs/2510.12765 https://…

Efficient Perceptual Image Super Resolution: AIM 2025 Study and Benchmark
This paper presents a comprehensive study and benchmark on Efficient Perceptual Super-Resolution (EPSR). While significant progress has been made in efficient PSNR-oriented super resolution, approaches focusing on perceptual quality metrics remain relatively inefficient. Motivated by this gap, we aim to replicate or improve the perceptual results of Real-ESRGAN while meeting strict efficiency constraints: a maximum of 5M parameters and 2000 GFLOPs, calculated for an input size of 960x540 pixels…

A Systematic Literature Review of Machine Learning Techniques for Observational Constraints in Cosmology
Luis Rojas, Sebasti\'an Espinoza, Esteban Gonz\'alez, Carlos Maldonado, Fei Luo
https://arxiv.org/abs/2510.09876

A Systematic Literature Review of Machine Learning Techniques for Observational Constraints in Cosmology
This paper presents a systematic literature review focusing on the application of machine learning techniques for deriving observational constraints in cosmology. The goal is to evaluate and synthesize existing research to identify effective methodologies, highlight gaps, and propose future research directions. Our review identifies several key findings: (1) various machine learning techniques, including Bayesian neural networks, Gaussian processes, and deep learning models, have been applied t…

EB-MBD: Emerging-Barrier Model-Based Diffusion for Safe Trajectory Optimization in Highly Constrained Environments
Raghav Mishra, Ian R. Manchester
https://arxiv.org/abs/2510.07700

EB-MBD: Emerging-Barrier Model-Based Diffusion for Safe Trajectory Optimization in Highly Constrained Environments
We propose enforcing constraints on Model-Based Diffusion by introducing emerging barrier functions inspired by interior point methods. We show that constraints on Model-Based Diffusion can lead to catastrophic performance degradation, even on simple 2D systems due to sample inefficiency in the Monte Carlo approximation of the score function. We introduce Emerging-Barrier Model-Based Diffusion (EB-MBD) which uses progressively introduced barrier constraints to avoid these problems, significantl…

Sequential Convex Programming for 6-DoF Powered Descent Guidance with Continuous-Time Compound State-Triggered Constraints
Samet Uzun, Behcet Acikmese, John M. Carson III
https://arxiv.org/abs/2510.09610

Sequential Convex Programming for 6-DoF Powered Descent Guidance with Continuous-Time Compound State-Triggered Constraints
This paper presents a sequential convex programming (SCP) framework for ensuring the continuous-time satisfaction of compound state-triggered constraints, a subset of logical specifications, in the powered descent guidance (PDG) problem. The proposed framework combines the generalized mean-based smooth robustness measure (D-GMSR), a parameterization technique tailored for expressing discrete-time temporal and logical specifications through smooth functions, with the continuous-time successive c…

Semi-infinite Nonconvex Constrained Min-Max Optimization
Cody Melcher, Zeinab Alizadeh, Lindsey Hiett, Afrooz Jalilzadeh, Erfan Yazdandoost Hamedani
https://arxiv.org/abs/2510.12007

Semi-infinite Nonconvex Constrained Min-Max Optimization
Semi-Infinite Programming (SIP) has emerged as a powerful framework for modeling problems with infinite constraints, however, its theoretical development in the context of nonconvex and large-scale optimization remains limited. In this paper, we investigate a class of nonconvex min-max optimization problems with nonconvex infinite constraints, motivated by applications such as adversarial robustness and safety-constrained learning. We propose a novel inexact dynamic barrier primal-dual algorith…

Entropy Regularizing Activation: Boosting Continuous Control, Large Language Models, and Image Classification with Activation as Entropy Constraints
Zilin Kang, Chonghua Liao, Tingqiang Xu, Huazhe Xu
https://arxiv.org/abs/2510.08549

Entropy Regularizing Activation: Boosting Continuous Control, Large Language Models, and Image Classification with Activation as Entropy Constraints
We propose ERA, a new paradigm that constrains the sampling entropy above given thresholds by applying specially designed activations to the outputs of models. Our approach demonstrates broad effectiveness across different domains: 1) for large language models(LLMs), boosting the AIME 2025 score for Qwen2.5-Math-7B by 37.4%; 2) for continuous control reinforcement learning agents, improving performance by more than 30% over strong baselines such as SAC on the challenging HumanoidBench; 3) for i…

Efficient Real-World Deblurring using Single Images: AIM 2025 Challenge Report
Daniel Feijoo, Paula Garrido-Mellado, Marcos V. Conde, Jaesung Rim, Alvaro Garcia, Sunghyun Cho, Radu Timofte
https://arxiv.org/abs/2510.12788

Efficient Real-World Deblurring using Single Images: AIM 2025 Challenge Report
This paper reviews the AIM 2025 Efficient Real-World Deblurring using Single Images Challenge, which aims to advance in efficient real-blur restoration. The challenge is based on a new test set based on the well known RSBlur dataset. Pairs of blur and degraded images in this dataset are captured using a double-camera system. Participant were tasked with developing solutions to effectively deblur these type of images while fulfilling strict efficiency constraints: fewer than 5 million model para…

The value of storage in electricity distribution: The role of storage
Dirk Lauinger, Deepjyoti Deka, Sungho Shin
https://arxiv.org/abs/2510.12435 https://a…

The value of storage in electricity distribution: The role of storage
Electricity distribution companies deploy battery storage to defer grid upgrades by reducing peak demand. In deregulated jurisdictions, such storage often sits idle because regulatory constraints bar participation in electricity markets. Here, we develop an optimization framework that, to our knowledge, provides the first formal model of market participation constraints within storage investment and operation planning. Applying the framework to a Massachusetts case study, we find that market pa…

Updated constraints on interacting dark energy: A comprehensive analysis using multiple CMB probes, DESI DR2, and supernovae observations
Tian-Nuo Li, Guo-Hong Du, Yun-He Li, Yichao Li, Jia-Le Ling, Jing-Fei Zhang, Xin Zhang
https://arxiv.org/abs/2510.11363

Updated constraints on interacting dark energy: A comprehensive analysis using multiple CMB probes, DESI DR2, and supernovae observations
Recent DESI baryon acoustic oscillation (BAO) measurements, combined with Planck cosmic microwave background (CMB) data and DESY5 type Ia supernova (SN) data, indicate a significant deviation from $Λ$CDM, which seems to suggest that this deviation can be explained by an interaction between dark energy and dark matter. In this work, we perform a comprehensive analysis by utilizing the latest DESI DR2 BAO data in conjunction with CMB data from ACT, SPT, Planck, and WMAP, along with SN data from …

Looking to Learn: Token-wise Dynamic Gating for Low-Resource Vision-Language Modelling
Bianca-Mihaela Ganescu, Suchir Salhan, Andrew Caines, Paula Buttery
https://arxiv.org/abs/2510.08470

Looking to Learn: Token-wise Dynamic Gating for Low-Resource Vision-Language Modelling
Training vision-language models on cognitively-plausible amounts of data requires rethinking how models integrate multimodal information. Within the constraints of the Vision track for the BabyLM Challenge 2025, we propose a lightweight decoder-based architecture with (1) token-wise dynamic gating for adaptive fusion of linguistic and visual cues, (2) feature modulation and channel attention to maximise the utility of limited visual information and (3) auxiliary contrastive objectives for visua…

What You Don't Know Can Hurt You: How Well do Latent Safety Filters Understand Partially Observable Safety Constraints?
Matthew Kim, Kensuke Nakamura, Andrea Bajcsy
https://arxiv.org/abs/2510.06492

What You Don't Know Can Hurt You: How Well do Latent Safety Filters Understand Partially Observable Safety Constraints?
Safe control techniques, such as Hamilton-Jacobi reachability, provide principled methods for synthesizing safety-preserving robot policies but typically assume hand-designed state spaces and full observability. Recent work has relaxed these assumptions via latent-space safe control, where state representations and dynamics are learned jointly through world models that reconstruct future high-dimensional observations (e.g., RGB images) from current observations and actions. This enables safety …

Empowering Prosumers: Incentive Design for Local Electricity Markets Under Generalized Uncertainty and Grid Constraints
P{\aa}l Forr Austnes, Matthieu Jacobs, Lu Wang, Mario Paolone
https://arxiv.org/abs/2510.12318

Empowering Prosumers: Incentive Design for Local Electricity Markets Under Generalized Uncertainty and Grid Constraints
Since the 1990s, widespread introduction of central (wholesale) electricity markets has been seen across multiple continents, driven by the search for efficient operation of the power grid through competition. The increase of renewables has made significant impacts both on central electricity markets and distribution-level grids as renewable power generation is often connected to the latter. These stochastic renewable technologies have both advantages and disadvantages. On one hand they offer v…

Heuristic Bundle Upper Bound Based Polyhedral Bundle Method for Semidefinite Programming
Zilong Cui, Ran Gu
https://arxiv.org/abs/2510.12374 https://arxiv.…

Heuristic Bundle Upper Bound Based Polyhedral Bundle Method for Semidefinite Programming
Semidefinite programming (SDP) is a fundamental class of convex optimization problems with diverse applications in mathematics, engineering, machine learning, and related disciplines. This paper investigates the application of the polyhedral bundle method to standard SDPs. The basic idea of this method is to approximate semidefinite constraints using linear constraints, and thereby transform the SDP problem into a series of quadratic programming subproblems. However, the number of linear constr…

Constraints on the interacting holographic dark energy models: implications from background and perturbations data
N. Nazari Pooya
https://arxiv.org/abs/2510.08875 https://

Constraints on the interacting holographic dark energy models: implications from background and perturbations data
In this study, we employ a two-step method to analyze models of holographic dark energy (HDE) and interacting holographic dark energy (IHDE), incorporating three distinct dark energy (DE)-dark matter (DM) interaction terms. First, using the latest background dataset, we conduct a Markov chain Monte Carlo (MCMC) analysis to constrain the free parameters of the models. Then, we assess the models against each other using the key background parameters and compare them to the $Λ$CDM standard model.…

Incoherent Imaging with Spatially Structured Quantum Probes
Anthony J. Brady, Zihao Gong, Alexey V. Gorshkov, Saikat Guha
https://arxiv.org/abs/2510.09521 https://

Incoherent Imaging with Spatially Structured Quantum Probes
Incoherent imaging, including fluorescence and absorption microscopy, is often limited by weak signals and resolution constraints -- notoriously, Rayleigh's curse. We investigate how spatially structured quantum probes, combined with quantum detection strategies like spatial mode demultiplexing and photon counting, overcome these limitations. We propose a novel imaging protocol based on twin-beam echoes that maps the generalized incoherent-imaging model -- comprising both absorption and fluores…

Bound on entanglement in neural quantum states
Nisarga Paul
https://arxiv.org/abs/2510.11797 https://arxiv.org/pdf/2510.11797

Bound on entanglement in neural quantum states
Variational wavefunctions offer a practical route around the exponential complexity of many-body Hilbert spaces, but their expressive power is often sharply constrained. Matrix product states, for instance, are efficient but limited to area law entangled states. Neural quantum states (NQS) are widely believed to overcome such limitations, yet little is known about their fundamental constraints. Here we prove that feed-forward neural quantum states acting on $n$ spins with $k$ scalar nonlinearit…

Decentralized CBF-based Safety Filters for Collision Avoidance of Cooperative Missile Systems with Input Constraints
Johannes Autenrieb, Mark Spiller
https://arxiv.org/abs/2510.06846

Decentralized CBF-based Safety Filters for Collision Avoidance of Cooperative Missile Systems with Input Constraints
This paper presents a decentralized safety filter for collision avoidance in multi-agent aerospace interception scenarios. The approach leverages robust control barrier functions (RCBFs) to guarantee forward invariance of safety sets under bounded inputs and high-relative-degree dynamics. Each effector executes its nominal cooperative guidance command, while a local quadratic program (QP) modifies the input only when necessary. Event-triggered activation based on range and zero-effort miss (ZEM…

Bandits with Single-Peaked Preferences and Limited Resources
Gur Keinan, Rotem Torkan, Omer Ben-Porat
https://arxiv.org/abs/2510.09425 https://arxiv.org/pd…

Bandits with Single-Peaked Preferences and Limited Resources
We study an online stochastic matching problem in which an algorithm sequentially matches $U$ users to $K$ arms, aiming to maximize cumulative reward over $T$ rounds under budget constraints. Without structural assumptions, computing the optimal matching is NP-hard, making online learning computationally infeasible. To overcome this barrier, we focus on \emph{single-peaked preferences} -- a well-established structure in social choice theory, where users' preferences are unimodal with respect to…

Adaptive Control Allocation for Underactuated Time-Scale Separated Non-Affine Systems
Daniel M. Cherenson, Dimitra Panagou
https://arxiv.org/abs/2510.07507 https://

Adaptive Control Allocation for Underactuated Time-Scale Separated Non-Affine Systems
Many robotic systems are underactuated, meaning not all degrees of freedom can be directly controlled due to lack of actuators, input constraints, or state-dependent actuation. This property, compounded by modeling uncertainties and disturbances, complicates the control design process for trajectory tracking. In this work, we propose an adaptive control architecture for uncertain, nonlinear, underactuated systems with input constraints. Leveraging time-scale separation, we construct a reduced-o…

Locally Optimal Private Sampling: Beyond the Global Minimax
Hrad Ghoukasian, Bonwoo Lee, Shahab Asoodeh
https://arxiv.org/abs/2510.09485 https://arxiv.org/…

Locally Optimal Private Sampling: Beyond the Global Minimax
We study the problem of sampling from a distribution under local differential privacy (LDP). Given a private distribution $P \in \mathcal{P}$, the goal is to generate a single sample from a distribution that remains close to $P$ in $f$-divergence while satisfying the constraints of LDP. This task captures the fundamental challenge of producing realistic-looking data under strong privacy guarantees. While prior work by Park et al. (NeurIPS'24) focuses on global minimax-optimality across a class …

Learning Social Navigation from Positive and Negative Demonstrations and Rule-Based Specifications
Chanwoo Kim, Jihwan Yoon, Hyeonseong Kim, Taemoon Jeong, Changwoo Yoo, Seungbeen Lee, Soohwan Byeon, Hoon Chung, Matthew Pan, Jean Oh, Kyungjae Lee, Sungjoon Choi
https://arxiv.org/abs/2510.12215

Learning Social Navigation from Positive and Negative Demonstrations and Rule-Based Specifications
Mobile robot navigation in dynamic human environments requires policies that balance adaptability to diverse behaviors with compliance to safety constraints. We hypothesize that integrating data-driven rewards with rule-based objectives enables navigation policies to achieve a more effective balance of adaptability and safety. To this end, we develop a framework that learns a density-based reward from positive and negative demonstrations and augments it with rule-based objectives for obstacle a…

Learning Robust Agile Flight Control with Stability Guarantees
Lukas Pries, Markus Ryll
https://arxiv.org/abs/2510.12611 https://arxiv.org/pdf/2510.12611…

Learning Robust Agile Flight Control with Stability Guarantees
In the evolving landscape of high-speed agile quadrotor flight, achieving precise trajectory tracking at the platform's operational limits is paramount. Controllers must handle actuator constraints, exhibit robustness to disturbances, and remain computationally efficient for safety-critical applications. In this work, we present a novel neural-augmented feedback controller for agile flight control. The controller addresses individual limitations of existing state-of-the-art control paradigms an…

Residual MPC: Blending Reinforcement Learning with GPU-Parallelized Model Predictive Control
Se Hwan Jeon, Ho Jae Lee, Seungwoo Hong, Sangbae Kim
https://arxiv.org/abs/2510.12717

Residual MPC: Blending Reinforcement Learning with GPU-Parallelized Model Predictive Control
Model Predictive Control (MPC) provides interpretable, tunable locomotion controllers grounded in physical models, but its robustness depends on frequent replanning and is limited by model mismatch and real-time computational constraints. Reinforcement Learning (RL), by contrast, can produce highly robust behaviors through stochastic training but often lacks interpretability, suffers from out-of-distribution failures, and requires intensive reward engineering. This work presents a GPU-paralleli…